Enhanced voice recognition task completion

ABSTRACT

A method for recognizing speech in a vehicle includes receiving speech at a microphone installed to a vehicle, and determining whether the speech includes a navigation instruction. If the speech includes a navigation instruction, the speech may be sent to a remote facility. After sending the speech to the remote facility, a local speech recognition result is provided in the vehicle to the user. The speech sent to the remote facility may be used to provide corrective action. A system for recognizing speech in a vehicle may include a microphone, and may be configured to determine a local speech recognition result from the speech command and determine when the speech command includes a navigation instruction. The system may further include a remote server in communication with the vehicle that receives a sample of the speech command from the speech recognition system when the speech command includes a navigation instruction.

TECHNICAL FIELD

The present invention relates to speech recognition systems for avehicle, and more particularly, to speech recognition systems thatrespond to a wide variety of commands, or commands that are otherwiseunpredictable.

INTRODUCTION

Voice recognition systems in vehicle are relied upon to handle anincreasing range of tasks. Some tasks, such as vehicle navigation,necessary entail a large number of non-standard or specializedinstructions such as street names, addresses, or names of points ofinterest, merely as examples. The large number of potential instructionsrequires robust speech recognition systems, as potential commands arevaried and unpredictable. Accordingly, voice recognition success ratesare typically lower. The relatively lower success rates typical ofnavigation systems may result in user frustration, and lower utilizationof the voice recognition system.

SUMMARY

In at least one example, a method of recognizing speech in a vehicleincludes receiving speech at a microphone installed to a vehicle, anddetermining whether the speech includes a navigation instruction. If thespeech includes a navigation instruction, the speech may be sent to aremote facility. After sending the speech to the remote facility, alocal speech recognition result, i.e., determined in the vehicle, isprovided in the vehicle to the user. In at least some implementationsdescribed herein, the speech sent to the remote facility may be used toprovide corrective action, for example, where the local speechrecognition result is inadequate or the user experiences difficulty withthe system.

In at least one implementation, a method of recognizing speech in avehicle includes determining a success rate of speech recognition in avoice recognition task is below a predetermined threshold. The methodmay further include receiving speech at a microphone installed to avehicle, and determining whether the speech is directed to the voicerecognition task. In response to the determination that the speech isdirected to the voice recognition task and that the success rateassociated with the voice recognition task is below the predeterminedthreshold, the speech may be sent to a remote facility. A local speechrecognition result in the vehicle after the speech is sent in step (c),the local speech recognition result determined in the vehicle. In atleast some implementations described herein, the speech sent to theremote facility may be used to provide corrective action, as notedabove.

In at least one example, a system for recognizing speech in a vehicleincludes a microphone installed in the vehicle that is configured toreceive a speech command from a user. The vehicle speech recognitionsystem may be configured to determine a local speech recognition resultfrom the speech command, and determine when the speech command includesa navigation instruction. The system may further include a remote serverin communication with the vehicle that is configured to receive a sampleof the speech command from the speech recognition system when the speechcommand includes a navigation instruction.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more embodiments of the invention will hereinafter be describedin conjunction with the appended drawings, wherein like designationsdenote like elements, and wherein:

FIG. 1 is a block diagram depicting an embodiment of a communicationssystem that is capable of utilizing the method disclosed herein; and

FIG. 2 is a block diagram depicting an embodiment of an automatic speechrecognition (ASR) system; and

FIG. 3 is a process flow diagram illustrating a process flow diagram foran example method of recognizing speech in a vehicle.

DETAILED DESCRIPTION OF THE ILLUSTRATED EMBODIMENT(S)

The example methods and systems described below may generally archivespeech or provide corrective assistance where speech recognition systemsare performing below a predetermined threshold. For example, where avehicle speech recognition system is required to recognizenon-standardized instructions such as formal names of contacts, streetnames, or other proper names, speech commands may be archived at thevehicle or sent to a remote facility. The speech commands that arearchived or sent to the remote facility may then be used upon thedetection of some user difficulty with the speech recognition system.Personnel at the remote facility may generally provide a backup orcorrective assistance upon a detection of a user having difficulty withthe speech recognition system. Moreover, speech may be archived or sentto the remote facility upon receipt in the vehicle, thereby allowingremote personnel to provide assistance as soon as a subsequent userdifficulty is observed.

Communications System—

With reference to FIG. 1, there is shown an operating environment thatcomprises a mobile vehicle communications system 10 and that can be usedto implement the method disclosed herein. Communications system 10generally includes a vehicle 12, one or more wireless carrier systems14, a land communications network 16, a computer 18, and a call center20. It should be understood that the disclosed method can be used withany number of different systems and is not specifically limited to theoperating environment shown here. Also, the architecture, construction,setup, and operation of the system 10 and its individual components aregenerally known in the art. Thus, the following paragraphs simplyprovide a brief overview of one such communications system 10; however,other systems not shown here could employ the disclosed method as well.

Vehicle 12 is depicted in the illustrated embodiment as a passenger car,but it should be appreciated that any other vehicle includingmotorcycles, trucks, sports utility vehicles (SUVs), recreationalvehicles (RVs), marine vessels, aircraft, etc., can also be used. Someof the vehicle electronics 28 is shown generally in FIG. 1 and includesa telematics unit 30, a microphone 32, one or more pushbuttons or othercontrol inputs 34, an audio system 36, a visual display 38, and a GPSmodule 40 as well as a number of other vehicle system modules (VSMs) 42.Some of these devices can be connected directly to the telematics unitsuch as, for example, the microphone 32 and pushbutton(s) 34, whereasothers are indirectly connected using one or more network connections,such as a communications bus 44 or an entertainment bus 46. Examples ofsuitable network connections include a controller area network (CAN), amedia oriented system transfer (MOST), a local interconnection network(LIN), a local area network (LAN), and other appropriate connectionssuch as Ethernet or others that conform with known ISO, SAE and IEEEstandards and specifications, to name but a few.

Telematics unit 30 is itself a vehicle system module (VSM) and can beimplemented as an OEM-installed (embedded) or aftermarket device that isinstalled in the vehicle and that enables wireless voice and/or datacommunication over wireless carrier system 14 and via wirelessnetworking. This enables the vehicle to communicate with call center 20,other telematics-enabled vehicles, or some other entity or device. Thetelematics unit preferably uses radio transmissions to establish acommunications channel (a voice channel and/or a data channel) withwireless carrier system 14 so that voice and/or data transmissions canbe sent and received over the channel. By providing both voice and datacommunication, telematics unit 30 enables the vehicle to offer a numberof different services including those related to navigation, telephony,emergency assistance, diagnostics, infotainment, etc. Data can be senteither via a data connection, such as via packet data transmission overa data channel, or via a voice channel using techniques known in theart. For combined services that involve both voice communication (e.g.,with a live advisor or voice response unit at the call center 20) anddata communication (e.g., to provide GPS location data or vehiclediagnostic data to the call center 20), the system can utilize a singlecall over a voice channel and switch as needed between voice and datatransmission over the voice channel, and this can be done usingtechniques known to those skilled in the art.

According to one embodiment, telematics unit 30 utilizes cellularcommunication according to either GSM, CDMA, or LTE standards and thusincludes a standard cellular chipset 50 for voice communications likehands-free calling, a wireless modem for data transmission, anelectronic processing device 52, one or more digital memory devices 54,and a dual antenna 56. It should be appreciated that the modem caneither be implemented through software that is stored in the telematicsunit and is executed by processor 52, or it can be a separate hardwarecomponent located internal or external to telematics unit 30. The modemcan operate using any number of different standards or protocols such asLTE, EVDO, CDMA, GPRS, and EDGE. Wireless networking between the vehicleand other networked devices can also be carried out using telematicsunit 30. For this purpose, telematics unit 30 can be configured tocommunicate wirelessly according to one or more wireless protocols,including short range wireless communication (SRWC) such as any of theIEEE 802.11 protocols, WiMAX, ZigBee™, Wi-Fi direct, Bluetooth™, or nearfield communication (NFC). When used for packet-switched datacommunication such as TCP/IP, the telematics unit can be configured witha static IP address or can be set up to automatically receive anassigned IP address from another device on the network such as a routeror from a network address server.

Processor 52 can be any type of device capable of processing electronicinstructions including microprocessors, microcontrollers, hostprocessors, controllers, vehicle communication processors, andapplication specific integrated circuits (ASICs). It can be a dedicatedprocessor used only for telematics unit 30 or can be shared with othervehicle systems. Processor 52 executes various types of digitally-storedinstructions, such as software or firmware programs stored in memory 54,which enable the telematics unit to provide a wide variety of services.For instance, processor 52 can execute programs or process data to carryout at least a part of the method discussed herein.

Telematics unit 30 can be used to provide a diverse range of vehicleservices that involve wireless communication to and/or from the vehicle.Such services include: turn-by-turn directions and othernavigation-related services that are provided in conjunction with theGPS-based vehicle navigation module 40; airbag deployment notificationand other emergency or roadside assistance-related services that areprovided in connection with one or more collision sensor interfacemodules such as a body control module (not shown); diagnostic reportingusing one or more diagnostic modules; and infotainment-related serviceswhere music, webpages, movies, television programs, videogames and/orother information is downloaded by an infotainment module (not shown)and is stored for current or later playback. The above-listed servicesare by no means an exhaustive list of all of the capabilities oftelematics unit 30, but are simply an enumeration of some of theservices that the telematics unit is capable of offering. Furthermore,it should be understood that at least some of the aforementioned modulescould be implemented in the form of software instructions saved internalor external to telematics unit 30, they could be hardware componentslocated internal or external to telematics unit 30, or they could beintegrated and/or shared with each other or with other systems locatedthroughout the vehicle, to cite but a few possibilities. In the eventthat the modules are implemented as VSMs 42 located external totelematics unit 30, they could utilize vehicle bus 44 to exchange dataand commands with the telematics unit.

GPS module 40 receives radio signals from a constellation 60 of GPSsatellites. From these signals, the module 40 can determine vehicleposition that is used for providing navigation and otherposition-related services to the vehicle driver. Navigation informationcan be presented on the display 38 (or other display within the vehicle)or can be presented verbally such as is done when supplying turn-by-turnnavigation. The navigation services can be provided using a dedicatedin-vehicle navigation module (which can be part of GPS module 40), orsome or all navigation services can be done via telematics unit 30,wherein the position information is sent to a remote location forpurposes of providing the vehicle with navigation maps, map annotations(points of interest, restaurants, etc.), route calculations, and thelike. The position information can be supplied to call center 20 orother remote computer system, such as computer 18, for other purposes,such as fleet management. Also, new or updated map data can bedownloaded to the GPS module 40 from the call center 20 via thetelematics unit 30.

Apart from the audio system 36 and GPS module 40, the vehicle 12 caninclude other vehicle system modules (VSMs) 42 in the form of electronichardware components that are located throughout the vehicle andtypically receive input from one or more sensors and use the sensedinput to perform diagnostic, monitoring, control, reporting and/or otherfunctions. Each of the VSMs 42 is preferably connected by communicationsbus 44 to the other VSMs, as well as to the telematics unit 30, and canbe programmed to run vehicle system and subsystem diagnostic tests. Asexamples, one VSM 42 can be an engine control module (ECM) that controlsvarious aspects of engine operation such as fuel ignition and ignitiontiming, another VSM 42 can be a powertrain control module that regulatesoperation of one or more components of the vehicle powertrain, andanother VSM 42 can be a body control module that governs variouselectrical components located throughout the vehicle, like the vehicle'spower door locks and headlights. According to one embodiment, the enginecontrol module is equipped with on-board diagnostic (OBD) features thatprovide myriad real-time data, such as that received from varioussensors including vehicle emissions sensors, and provide a standardizedseries of diagnostic trouble codes (DTCs) that allow a technician torapidly identify and remedy malfunctions within the vehicle. As isappreciated by those skilled in the art, the above-mentioned VSMs areonly examples of some of the modules that may be used in vehicle 12, asnumerous others are also possible.

Vehicle electronics 28 also includes a number of vehicle user interfacesthat provide vehicle occupants with a means of providing and/orreceiving information, including microphone 32, pushbutton(s) 34, audiosystem 36, and visual display 38. As used herein, the term ‘vehicle userinterface’ broadly includes any suitable form of electronic device,including both hardware and software components, which is located on thevehicle and enables a vehicle user to communicate with or through acomponent of the vehicle. Microphone 32 provides audio input to thetelematics unit to enable the driver or other occupant to provide voicecommands and carry out hands-free calling via the wireless carriersystem 14. For this purpose, it can be connected to an on-boardautomated voice processing unit utilizing human-machine interface (HMI)technology known in the art. The pushbutton(s) 34 allow manual userinput into the telematics unit 30 to initiate wireless telephone callsand provide other data, response, or control input. Separate pushbuttonscan be used for initiating emergency calls versus regular serviceassistance calls to the call center 20. Audio system 36 provides audiooutput to a vehicle occupant and can be a dedicated, stand-alone systemor part of the primary vehicle audio system. According to the particularembodiment shown here, audio system 36 is operatively coupled to bothvehicle bus 44 and entertainment bus 46 and can provide AM, FM andsatellite radio, CD, DVD and other multimedia functionality. Thisfunctionality can be provided in conjunction with or independent of theinfotainment module described above. Visual display 38 is preferably agraphics display, such as a touch screen on the instrument panel or aheads-up display reflected off of the windshield, and can be used toprovide a multitude of input and output functions. Various other vehicleuser interfaces can also be utilized, as the interfaces of FIG. 1 areonly an example of one particular implementation.

Wireless carrier system 14 is preferably a cellular telephone systemthat includes a plurality of cell towers 70 (only one shown), one ormore mobile switching centers (MSCs) 72, as well as any other networkingcomponents required to connect wireless carrier system 14 with landnetwork 16. Each cell tower 70 includes sending and receiving antennasand a base station, with the base stations from different cell towersbeing connected to the MSC 72 either directly or via intermediaryequipment such as a base station controller. Cellular system 14 canimplement any suitable communications technology, including for example,analog technologies such as AMPS, or the newer digital technologies suchas CDMA (e.g., CDMA2000) or GSM/GPRS. As will be appreciated by thoseskilled in the art, various cell tower/base station/MSC arrangements arepossible and could be used with wireless system 14. For instance, thebase station and cell tower could be co-located at the same site or theycould be remotely located from one another, each base station could beresponsible for a single cell tower or a single base station couldservice various cell towers, and various base stations could be coupledto a single MSC, to name but a few of the possible arrangements.

Apart from using wireless carrier system 14, a different wirelesscarrier system in the form of satellite communication can be used toprovide uni-directional or bi-directional communication with thevehicle. This can be done using one or more communication satellites 62and an uplink transmitting station 64. Uni-directional communication canbe, for example, satellite radio services, wherein programming content(news, music, etc.) is received by transmitting station 64, packaged forupload, and then sent to the satellite 62, which broadcasts theprogramming to subscribers. Bi-directional communication can be, forexample, satellite telephony services using satellite 62 to relaytelephone communications between the vehicle 12 and station 64. If used,this satellite telephony can be utilized either in addition to or inlieu of wireless carrier system 14.

Land network 16 may be a conventional land-based telecommunicationsnetwork that is connected to one or more landline telephones andconnects wireless carrier system 14 to call center 20. For example, landnetwork 16 may include a public switched telephone network (PSTN) suchas that used to provide hardwired telephony, packet-switched datacommunications, and the Internet infrastructure. One or more segments ofland network 16 could be implemented through the use of a standard wirednetwork, a fiber or other optical network, a cable network, power lines,other wireless networks such as wireless local area networks (WLANs), ornetworks providing broadband wireless access (BWA), or any combinationthereof. Furthermore, call center 20 need not be connected via landnetwork 16, but could include wireless telephony equipment so that itcan communicate directly with a wireless network, such as wirelesscarrier system 14.

Computer 18 can be one of a number of computers accessible via a privateor public network such as the Internet. Each such computer 18 can beused for one or more purposes, such as a web server accessible by thevehicle via telematics unit 30 and wireless carrier 14. Other suchaccessible computers 18 can be, for example: a service center computerwhere diagnostic information and other vehicle data can be uploaded fromthe vehicle via the telematics unit 30; a client computer used by thevehicle owner or other subscriber for such purposes as accessing orreceiving vehicle data or to setting up or configuring subscriberpreferences or controlling vehicle functions; or a third partyrepository to or from which vehicle data or other information isprovided, whether by communicating with the vehicle 12 or call center20, or both. A computer 18 can also be used for providing Internetconnectivity such as DNS services or as a network address server thatuses DHCP or other suitable protocol to assign an IP address to thevehicle 12.

Call center 20 is designed to provide the vehicle electronics 28 with anumber of different system back-end functions and, according to theexemplary embodiment shown here, generally includes one or more switches80, servers 82, databases 84, live advisors 86, as well as an automatedvoice response system (VRS) 88, all of which are known in the art. Thesevarious call center components are preferably coupled to one another viaa wired or wireless local area network 90. Switch 80, which can be aprivate branch exchange (PBX) switch, routes incoming signals so thatvoice transmissions are usually sent to either the live adviser 86 byregular phone or to the automated voice response system 88 using VoIP.The live advisor phone can also use VoIP as indicated by the broken linein FIG. 1. VoIP and other data communication through the switch 80 isimplemented via a modem (not shown) connected between the switch 80 andnetwork 90. Data transmissions are passed via the modem to server 82and/or database 84. Database 84 can store account information such assubscriber authentication information, vehicle identifiers, profilerecords, behavioral patterns, and other pertinent subscriberinformation. Data transmissions may also be conducted by wirelesssystems, such as 802.11x, GPRS, and the like. Although the illustratedembodiment has been described as it would be used in conjunction with amanned call center 20 using live advisor 86, it will be appreciated thatthe call center can instead utilize VRS 88 as an automated advisor or, acombination of VRS 88 and the live advisor 86 can be used.

Turning now to FIG. 2, there is shown an illustrative architecture foran ASR system 210 that can be used to enable the presently disclosedmethod. In general, a vehicle occupant vocally interacts with anautomatic speech recognition system (ASR) for one or more of thefollowing fundamental purposes: training the system to understand avehicle occupant's particular voice; storing discrete speech such as aspoken nametag or a spoken control word like a numeral or keyword; orrecognizing the vehicle occupant's speech for any suitable purpose suchas voice dialing, menu navigation, transcription, service requests,vehicle device or device function control, or the like. Generally, ASRextracts acoustic data from human speech, compares and contrasts theacoustic data to stored subword data, selects an appropriate subwordwhich can be concatenated with other selected subwords, and outputs theconcatenated subwords or words for post-processing such as dictation ortranscription, address book dialing, storing to memory, training ASRmodels or adaptation parameters, or the like.

ASR systems are generally known to those skilled in the art, and FIG. 2illustrates just one specific illustrative ASR system 210. The system210 includes a device to receive speech such as the telematicsmicrophone 32, and an acoustic interface 33 such as a sound card of thetelematics unit 30 having an analog to digital converter to digitize thespeech into acoustic data. The system 210 also includes a memory such asthe telematics memory 54 for storing the acoustic data and storingspeech recognition software and databases, and a processor such as thetelematics processor 52 to process the acoustic data. The processorfunctions with the memory and in conjunction with the following modules:one or more front-end processors or pre-processor software modules 212for parsing streams of the acoustic data of the speech into parametricrepresentations such as acoustic features; one or more decoder softwaremodules 214 for decoding the acoustic features to yield digital subwordor word output data corresponding to the input speech utterances; andone or more post-processor software modules 216 for using the outputdata from the decoder module(s) 214 for any suitable purpose.

The system 210 can also receive speech from any other suitable audiosource(s) 31, which can be directly communicated with the pre-processorsoftware module(s) 212 as shown in solid line or indirectly communicatedtherewith via the acoustic interface 33. The audio source(s) 31 caninclude, for example, a telephonic source of audio such as a voice mailsystem, or other telephonic services of any kind.

One or more modules or models can be used as input to the decodermodule(s) 214. First, grammar and/or lexicon model(s) 218 can providerules governing which words can logically follow other words to formvalid sentences. In a broad sense, a grammar can define a universe ofvocabulary the system 210 expects at any given time in any given ASRmode. For example, if the system 210 is in a training mode for trainingcommands, then the grammar model(s) 218 can include all commands knownto and used by the system 210. In another example, if the system 210 isin a main menu mode, then the active grammar model(s) 218 can includeall main menu commands expected by the system 210 such as call, dial,exit, delete, directory, or the like. Second, acoustic model(s) 220assist with selection of most likely subwords or words corresponding toinput from the pre-processor module(s) 212. Third, word model(s) 222 andsentence/language model(s) 224 provide rules, syntax, and/or semanticsin placing the selected subwords or words into word or sentence context.Also, the sentence/language model(s) 224 can define a universe ofsentences the system 210 expects at any given time in any given ASRmode, and/or can provide rules, etc., governing which sentences canlogically follow other sentences to form valid extended speech.

According to an alternative illustrative embodiment, some or all of theASR system 210 can be resident on, and processed using, computingequipment in a location remote from the vehicle 12 such as the callcenter 20. For example, grammar models, acoustic models, and the likecan be stored in memory of one of the servers 82 and/or databases 84 inthe call center 20 and communicated to the vehicle telematics unit 30for in-vehicle speech processing. Similarly, speech recognition softwarecan be processed using processors of one of the servers 82 in the callcenter 20. In other words, the ASR system 210 can be resident in thetelematics unit 30, distributed across the call center 20 and thevehicle 12 in any desired manner, and/or resident at the call center 20.

First, acoustic data is extracted from human speech wherein a vehicleoccupant speaks into the microphone 32, which converts the utterancesinto electrical signals and communicates such signals to the acousticinterface 33. A sound-responsive element in the microphone 32 capturesthe occupant's speech utterances as variations in air pressure andconverts the utterances into corresponding variations of analogelectrical signals such as direct current or voltage. The acousticinterface 33 receives the analog electrical signals, which are firstsampled such that values of the analog signal are captured at discreteinstants of time, and are then quantized such that the amplitudes of theanalog signals are converted at each sampling instant into a continuousstream of digital speech data. In other words, the acoustic interface 33converts the analog electrical signals into digital electronic signals.The digital data are binary bits which are buffered in the telematicsmemory 54 and then processed by the telematics processor 52 or can beprocessed as they are initially received by the processor 52 inreal-time.

Second, the pre-processor module(s) 212 transforms the continuous streamof digital speech data into discrete sequences of acoustic parameters.More specifically, the processor 52 executes the pre-processor module(s)212 to segment the digital speech data into overlapping phonetic oracoustic frames of, for example, 10-30 ms duration. The framescorrespond to acoustic subwords such as syllables, demi-syllables,phones, diphones, phonemes, or the like. The pre-processor module(s) 212also performs phonetic analysis to extract acoustic parameters from theoccupant's speech such as time-varying feature vectors, from within eachframe. Utterances within the occupant's speech can be represented assequences of these feature vectors. For example, and as known to thoseskilled in the art, feature vectors can be extracted and can include,for example, vocal pitch, energy profiles, spectral attributes, and/orcepstral coefficients that can be obtained by performing Fouriertransforms of the frames and decorrelating acoustic spectra using cosinetransforms. Acoustic frames and corresponding parameters covering aparticular duration of speech are concatenated into unknown test patternof speech to be decoded.

Third, the processor executes the decoder module(s) 214 to process theincoming feature vectors of each test pattern. The decoder module(s) 214is also known as a recognition engine or classifier, and uses storedknown reference patterns of speech. Like the test patterns, thereference patterns are defined as a concatenation of related acousticframes and corresponding parameters. The decoder module(s) 214 comparesand contrasts the acoustic feature vectors of a subword test pattern tobe recognized with stored subword reference patterns, assesses themagnitude of the differences or similarities therebetween, andultimately uses decision logic to choose a best matching subword as therecognized subword. In general, the best matching subword is that whichcorresponds to the stored known reference pattern that has a minimumdissimilarity to, or highest probability of being, the test pattern asdetermined by any of various techniques known to those skilled in theart to analyze and recognize subwords. Such techniques can includedynamic time-warping classifiers, artificial intelligence techniques,neural networks, free phoneme recognizers, and/or probabilistic patternmatchers such as Hidden Markov Model (HMM) engines.

HMM engines are known to those skilled in the art for producing multiplespeech recognition model hypotheses of acoustic input. The hypothesesare considered in ultimately identifying and selecting that recognitionoutput which represents the most probable correct decoding of theacoustic input via feature analysis of the speech. More specifically, anHMM engine generates statistical models in the form of an “N-best” listof subword model hypotheses ranked according to HMM-calculatedconfidence values or probabilities of an observed sequence of acousticdata given one or another subword such as by the application of Bayes'Theorem.

A Bayesian HMM process identifies a best hypothesis corresponding to themost probable utterance or subword sequence for a given observationsequence of acoustic feature vectors, and its confidence values candepend on a variety of factors including acoustic signal-to-noise ratiosassociated with incoming acoustic data. The HMM can also include astatistical distribution called a mixture of diagonal Gaussians, whichyields a likelihood score for each observed feature vector of eachsubword, which scores can be used to reorder the N-best list ofhypotheses. The HMM engine can also identify and select a subword whosemodel likelihood score is highest.

In a similar manner, individual HMMs for a sequence of subwords can beconcatenated to establish single or multiple word HMM. Thereafter, anN-best list of single or multiple word reference patterns and associatedparameter values may be generated and further evaluated.

In one example, the speech recognition decoder 214 processes the featurevectors using the appropriate acoustic models, grammars, and algorithmsto generate an N-best list of reference patterns. As used herein, theterm reference patterns is interchangeable with models, waveforms,templates, rich signal models, exemplars, hypotheses, or other types ofreferences. A reference pattern can include a series of feature vectorsrepresentative of one or more words or subwords and can be based onparticular speakers, speaking styles, and audible environmentalconditions. Those skilled in the art will recognize that referencepatterns can be generated by suitable reference pattern training of theASR system and stored in memory. Those skilled in the art will alsorecognize that stored reference patterns can be manipulated, whereinparameter values of the reference patterns are adapted based ondifferences in speech input signals between reference pattern trainingand actual use of the ASR system. For example, a set of referencepatterns trained for one vehicle occupant or certain acoustic conditionscan be adapted and saved as another set of reference patterns for adifferent vehicle occupant or different acoustic conditions, based on alimited amount of training data from the different vehicle occupant orthe different acoustic conditions. In other words, the referencepatterns are not necessarily fixed and can be adjusted during speechrecognition.

Using the in-vocabulary grammar and any suitable decoder algorithm(s)and acoustic model(s), the processor accesses from memory severalreference patterns interpretive of the test pattern. For example, theprocessor can generate, and store to memory, a list of N-best vocabularyresults or reference patterns, along with corresponding parametervalues. Illustrative parameter values can include confidence scores ofeach reference pattern in the N-best list of vocabulary and associatedsegment durations, likelihood scores, signal-to-noise ratio (SNR)values, and/or the like. The N-best list of vocabulary can be ordered bydescending magnitude of the parameter value(s). For example, thevocabulary reference pattern with the highest confidence score is thefirst best reference pattern, and so on. Once a string of recognizedsubwords are established, they can be used to construct words with inputfrom the word models 222 and to construct sentences with the input fromthe language models 224.

Finally, the post-processor software module(s) 216 receives the outputdata from the decoder module(s) 214 for any suitable purpose. In oneexample, the post-processor software module(s) 216 can identify orselect one of the reference patterns from the N-best list of single ormultiple word reference patterns as recognized speech. In anotherexample, the post-processor module(s) 216 can be used to convertacoustic data into text or digits for use with other aspects of the ASRsystem or other vehicle systems. In a further example, thepost-processor module(s) 216 can be used to provide training feedback tothe decoder 214 or pre-processor 212. More specifically, thepost-processor 216 can be used to train acoustic models for the decodermodule(s) 214, or to train adaptation parameters for the pre-processormodule(s) 212.

The method or parts thereof can be implemented in a computer programproduct embodied in a computer readable medium and includinginstructions usable by one or more processors of one or more computersof one or more systems to cause the system(s) to implement one or moreof the method steps. The computer program product may include one ormore software programs comprised of program instructions in source code,object code, executable code or other formats; one or more firmwareprograms; or hardware description language (HDL) files; and any programrelated data. The data may include data structures, look-up tables, ordata in any other suitable format. The program instructions may includeprogram modules, routines, programs, objects, components, and/or thelike. The computer program can be executed on one computer or onmultiple computers in communication with one another.

The program(s) can be embodied on computer readable media, which can benon-transitory and can include one or more storage devices, articles ofmanufacture, or the like. Exemplary computer readable media includecomputer system memory, e.g. RAM (random access memory), ROM (read onlymemory); semiconductor memory, e.g. EPROM (erasable, programmable ROM),EEPROM (electrically erasable, programmable ROM), flash memory; magneticor optical disks or tapes; and/or the like. The computer readable mediummay also include computer to computer connections, for example, whendata is transferred or provided over a network or another communicationsconnection (either wired, wireless, or a combination thereof). Anycombination(s) of the above examples is also included within the scopeof the computer-readable media. It is therefore to be understood thatthe method can be at least partially performed by any electronicarticles and/or devices capable of carrying out instructionscorresponding to one or more steps of the disclosed method.

Method—

Turning now to FIG. 3, a process flow diagram for an example method ofcompleting a speech recognition task is shown. Process 300 may begin atblock 305, where a speech command is received in the vehicle 12. Forexample, speech may be received at microphone 52 installed in or to thevehicle 12.

Proceeding to block 310, process 300 may determine whether correctiveassistance may be needed in a speech recognition system or subsystem. Insome examples, performance below a given threshold over time may be usedto determine that corrective assistance would be beneficial. Morespecifically, an accuracy rate of an ASR system, e.g., of the vehicle12, may be below a prescribed threshold or there may be some otherindication of consistent user difficulty.

In some examples, block 310 may simply query whether the domain of thespeech command is one that typically suffers from reduced performance oraccuracy, such as navigation or other speech domains that employ propernames, street names, city names, etc. In such examples, the vehicle 12may use any means that is convenient to determine whether the domain ofthe speech relates to navigation. Merely as examples, the speech may beanalyzed to determine the presence of an address, a point of interest,or other characteristics typical of a navigation speech command.

If the result of the query at block 310 is that corrective assistance isnot needed, or the domain is not navigation, process 300 may proceed toblock 315, where a standard speech recognition flow or logic is used,i.e., without archiving the speech command as described further below inblocks 320-345. From block 315, process 300 may then terminate.

Alternatively, if the result of the query at block 310 is thatcorrective assistance is needed or would be useful, or the domain of thespeech command is navigation, then process 300 may proceed to block 320.At block 320, the speech command may be archived, e.g., at the vehicle12. Merely as examples, the speech command may be archived as an .ogg or.wav file and may be stored in a memory installed in the vehicle 12,e.g., as part of the telematics unit 30 or in ASR system 210. Archivedspeech may be used to improve recognition of speech, at least insubsequent speech recognition sessions. For example, in a subsequentspeech recognition session at the vehicle 12, archived speech may beused to quickly compare to the subsequent speech. In this manner,vehicle 12 may provide improved speech recognition relatively quickly,and without needing to rely upon resources remote from the vehicle 12,e.g., as provided by remote facility 80. In some example approaches, theuse of in-vehicle resources such as the archived speech may be usedsolely in speech recognition domains where accuracy or customersatisfaction is problematic, such as navigation. Process 300 may thenproceed to block 325.

At block 325, the archived speech command may be sent to the remotefacility 80. The speech command may be sent to the remote facility 80 inany manner that is convenient. For example, it may be desirable tocompress or otherwise minimize a size of the archived speech commandbefore sending to the remote facility 80, thereby reducing bandwidthusage of the vehicle 12.

Proceeding to block 330, the vehicle 12 may perform local speechrecognition on the speech command, i.e., using the speech recognitionsystem of vehicle 12 described above in FIG. 2, and present results tothe user of the vehicle 12. Process 300 may then proceed to block 335.

At block 335, process 300 may query whether the speech recognitionresults presented at block 330 adequately represented the intendedspeech command. For example, the vehicle 12 may determine whether theuser of the vehicle 12 immediately accepted one of the presentedresults, indicating a successful recognition result, or instead had somedifficulty with the results as presented. If the user rejected theresults, or repeated the request, or repeated the request apredetermined number of times, this may provide an indication that theresults of the speech recognition were not correct. Process 300 mayproceed to block 345 if it is determined the recognition results werenot correct or the user had some difficulty with the results.

Generally, block 335 may use analysis of how a user of the vehicle 12responds to the speech recognition results presented at block 330 todetermine whether the speech recognition results presented to the userwere adequate. Where the user response indicates some difficulty withthe results, e.g., by rejecting the results one or more times, orterminating the speech command session before it is successfullycompleted, process 300 may determine that the speech recognition resultsdid not adequately capture the intended speech command.

Accordingly, where it is determined that the user has had somedifficulty with the presented results, at block 345 a route request maybe offered or transmitted to the vehicle 12 by the remote facility 80.For example, personnel of the remote facility 80 may be notified of thedifficulty that the user had in the vehicle 12 and may analyze thecompressed speech command that was sent to the remote facility 80. Thepersonnel may review the speech command, e.g., by way of the archivedcommand already sent to the remote facility at blocks 320/325, anddetermine the intended request. Moreover, in some examples the remotefacility 80 may review a record of archived speech received from thevehicle 12. Accordingly, in the case where certain phrases or commandshave resulted in a number of failures of the ASR system in the vehicle12, the remote facility 80 may review a history of previous commands todetermine corrective action or particular commands that the ASR systemof the vehicle 12 does not accurately identify. The remote facility 80may transmit a result intended to answer the intended speech commanddirectly to the vehicle 12. For example, the remote facility 80 may beused to provide navigation services, e.g., by providing turn-by-turndirections to the vehicle 12, since the vehicle 12 did not properlydetermine what the user request was. In this manner, where the user hassome difficulty with a speech command, the user may generallyautomatically receive a route request or information that is likely toanswer their initial query. Process 300 may then terminate.

If the recognition results presented to the user at block 330 aredetermined at block 335 to have been accepted by the user, or otherwisepresented without substantial difficulty of the user, process 300 mayproceed to block 340. At block 340, the navigation task is completedthrough an ordinary speech recognition process, i.e., the remoteanalysis of the archived navigation command need not be analyzed bypersonnel at the remote facility 80. Thus, the speech recognitionrequest, e.g., for navigation assistance, can be satisfied completelyusing on-board resources of the vehicle 12, e.g., GPS and map data.

It is to be understood that the foregoing is a description of one ormore embodiments of the invention. The invention is not limited to theparticular embodiment(s) disclosed herein, but rather is defined solelyby the claims below. Furthermore, the statements contained in theforegoing description relate to particular embodiments and are not to beconstrued as limitations on the scope of the invention or on thedefinition of terms used in the claims, except where a term or phrase isexpressly defined above. Various other embodiments and various changesand modifications to the disclosed embodiment(s) will become apparent tothose skilled in the art. All such other embodiments, changes, andmodifications are intended to come within the scope of the appendedclaims.

As used in this specification and claims, the terms “e.g.,” “forexample,” “for instance,” “such as,” and “like,” and the verbs“comprising,” “having,” “including,” and their other verb forms, whenused in conjunction with a listing of one or more components or otheritems, are each to be construed as open-ended, meaning that the listingis not to be considered as excluding other, additional components oritems. Other terms are to be construed using their broadest reasonablemeaning unless they are used in a context that requires a differentinterpretation.

What is claimed is:
 1. A method of recognizing speech in a vehicle,comprising the steps of: (a) receiving a first speech at a microphoneinstalled to a vehicle and converting the first speech to first digitaldata; (b) determining whether the first speech includes a navigationinstruction; (c) when the first speech is determined to include anavigation instruction, determining a recognition result for the firstspeech using an archive speech recognition process, including: (c1)archiving the first speech at the vehicle, and sending the first digitaldata representing the first speech to a remote facility; and (c2)providing a local speech recognition result in the vehicle after thefirst speech is sent in step (c1), wherein the local speech recognitionresult is determined in the vehicle; and (d) when the first speech isdetermined to not include a navigation instruction, determining therecognition result for the first speech using a standard speechrecognition process without archiving the first speech; (e) receivingfrom the remote facility a remote digital data representing a remoterecognition result for the first speech, and storing the remoterecognition result at the vehicle; (f) receiving at least a secondspeech at the microphone after the remote recognition result is storedat the vehicle and converting the second speech to second digital data;(g) determining whether the second speech includes a navigationinstruction; (h) when the second speech is determined to not include anavigation instruction, determining the recognition result for thesecond speech using a standard speech recognition process withoutarchiving the second speech; and (i) when the second speech isdetermined to include a navigation instruction, determining arecognition result for the second speech using the archive speechrecognition process, including: (i1) archiving the second speech at thevehicle, and sending the second digital data representing the secondspeech to the remote facility; and (i2) providing a local speechrecognition result in the vehicle using at least the received remoterecognition result, for the first speech wherein the local speechrecognition result is determined in the vehicle.
 2. The method of claim1, further comprising determining that the local speech recognitionresult has been rejected, and receiving the remote recognition result asa corrective recognition result at the vehicle, the correctiverecognition result being based upon the speech sent to the remotefacility.
 3. The method of claim 1, further comprising archiving atleast one of the first and second speech at the vehicle.
 4. The methodof claim 3, further comprising using the archived one of the first andsecond speech to identify a navigation instruction in a subsequentspeech received at the microphone.
 5. The method of claim 3, furthercomprising the step: (i) comparing the one of the first and secondspeech archived in step (c) with a third speech received subsequent tothe first and second speech at the microphone.
 6. The method of claim 5,further comprising determining that a same navigation instruction as theone of the first and second speech is being attempted in the thirdspeech based at least upon the comparison in step (i).
 7. The method ofclaim 1, wherein the first and second speech sent in steps (c1) and(i1), respectively, each includes a digital representation of an analogsample of the first and second speech received in steps (a) and (f),respectively.
 8. The method of claim 1, further comprising archiving aplurality of archived speech samples received from the vehicle at theremote facility.
 9. The method of claim 8, wherein the plurality ofarchived speech is used to identify a navigation instruction in asubsequent speech received at the microphone.
 10. The method of claim 1,further comprising determining a success rate of speech recognition in areduced performance voice recognition task is below a predeterminedthreshold over time in a plurality of speech recognition sessions,wherein the archive speech recognition process is used and the first andsecond speech is sent to the remote facility in response to thedetermination that the success rate is below the predeterminedthreshold.
 11. The method of claim 1, further comprising determiningwhether a speech result provided in response to at least one of thefirst and second speech is accepted by a vehicle user.
 12. The method ofclaim 11, further comprising completing a request in the speech usingresources on-board the vehicle when it is determined that the speechresult was accepted by the vehicle user.
 13. The method of claim 11,further comprising completing a request in the speech using resourcesreceived from the remote facility when it is determined that the speechresult was not accepted by the vehicle user.
 14. A method of recognizingspeech in a vehicle, comprising the steps of: (a) determining a successrate of speech recognition in a reduced performance voice recognitiontask is below a predetermined threshold over time in a plurality ofspeech recognition sessions; (b) receiving a first speech at amicrophone installed to a vehicle; (c) determining whether the firstspeech is directed to the reduced performance voice recognition task;(d) in response to the determinations in steps (a) and (c), when thespeech is directed to the reduced performance voice recognition task,determining a recognition result for the first speech using an archivespeech recognition process, including; and (d1) archiving the firstspeech at the vehicle, and sending the first speech to a remotefacility; and (d2) providing a local speech recognition result in thevehicle after the first speech is sent in step (d1), wherein the localspeech recognition result is determined in the vehicle; (e) when thefirst speech is determined to not be directed to the reduced performancevoice recognition task, determining the recognition result for the firstspeech using a standard speech recognition process without archiving thefirst speech; (f) receiving from the remote facility a remoterecognition result for the first speech, and storing the remoterecognition result at the vehicle; (g) receiving at least a secondspeech at the microphone after the remote recognition result is storedat the vehicle; (h) determining whether the second speech is directed tothe reduced performance voice recognition task; (i) when the secondspeech is determined to not be directed to the reduced performance voicerecognition task, determining the recognition result for the secondspeech using a standard speech recognition process without archiving thesecond speech; and (j) when the second speech is determined to bedirected to the reduced performance voice recognition task, determininga recognition result for the second speech using the archive speechrecognition process, including: (j1) archiving the second speech at thevehicle, and sending the second speech to the remote facility; and (j2)providing a local speech recognition result in the vehicle using atleast the received remote recognition result, for the first speechwherein the local speech recognition result is determined in thevehicle.
 15. The method of claim 14, wherein the reduced performancevoice recognition task is a navigation task.
 16. The method of claim 14,further comprising determining that the local speech recognition resulthas been rejected, and receiving the remote recognition result as acorrective recognition result at the vehicle, the corrective recognitionresult being based upon the speech sent to the remote facility.
 17. Themethod of claim 14, further comprising archiving at least one of thefirst and second speech at the vehicle.
 18. The method of claim 17,further comprising using the archived one of the first and second speechto identify a navigation instruction in a subsequent speech received atthe microphone.
 19. A system for recognizing speech in a vehicle,comprising: a speech recognition system installed in the vehicle, thespeech recognition system including a microphone configured to receive afirst speech command from a user and convert the first speech to firstdigital data, the speech recognition system configured to determine whenthe first speech command includes a navigation instruction; and a remoteserver in communication with the vehicle; wherein when the speechrecognition system determines the first speech command includes anavigation instruction, the speech recognition system is configured todetermine a recognition result for the first speech command using anarchive speech recognition process, including: archiving the firstspeech command at the vehicle, and sending the first digital datarepresenting the first speech command to the remote server; andproviding a local speech recognition result in the vehicle after thefirst speech command is sent, wherein the local speech recognitionresult is determined in the vehicle; wherein when the speech recognitionsystem determines the first speech command does not include a navigationinstruction, the speech recognition system is configured to determinethe recognition result for the first speech command using a standardspeech recognition process without archiving the first speech command;wherein the remote server is configured to receive from the speechrecognition system a remote digital data representing a remoterecognition result for the first speech command, the remote serverconfigured to send the remote recognition result to the vehicle; whereinthe speech recognition system is configured to receive at least a secondspeech command at the microphone after the remote recognition result isstored at the vehicle and convert the second speech command to seconddigital data, the speech recognition system configured to determinewhether the second speech command includes a navigation instruction;wherein when the second speech command is determined to not include anavigation instruction, the speech recognition system is configured todetermine the recognition result for the second speech using a standardspeech recognition process without archiving the second speech; andwherein when the second speech command is determined to include anavigation instruction, the speech recognition system is configured todetermine a recognition result for the second speech using the archivespeech recognition process, including: archiving the second speech atthe vehicle, and sending the second digital data representing the secondspeech to the remote server; and providing a local speech recognitionresult in the vehicle using at least the received remote recognitionresult, for the first speech wherein the local speech recognition resultis determined in the vehicle.